In [7]:
import sys
sys.path.insert(0,'../src/')
from data.make_dataset import *
from visualization.visualize import *
from models.models import *
%load_ext autoreload
%autoreload 1
The autoreload extension is already loaded. To reload it, use: %reload_ext autoreload
In [8]:
import torch
import numpy
if torch.cuda.is_available():
prop = torch.cuda.get_device_properties(0)
print(f"Using {prop.name} with {np.round(prop.total_memory/1e9, 2)}GB of RAM")
else:
print("Using CPU")
Using GeForce GTX 1060 with Max-Q Design with 6.37GB of RAM
Load Data¶
In [9]:
channel_size = 3
image_size = 64
batch_size = 128
workers = 10
In [10]:
%%time
data_loader = make_dataloader("../data/raw/planctons_original", image_size, batch_size, workers)
CPU times: user 6.1 ms, sys: 3.91 ms, total: 10 ms Wall time: 9.46 ms
Visualize Data¶
In [ ]:
print_samples(data_loader)
Load Models¶
In [14]:
latent_size = 100
feature_map_size = 64
In [15]:
beta = 0.5
lr = 0.0002
num_epochs = 2
In [16]:
g = DCGAN_Generator(latent_size, feature_map_size, channel_size)
d = DCGAN_Discriminator(feature_map_size, channel_size)
gan = GAN(d, g, lr, beta)
Train Model¶
In [17]:
%%time
gan.train(data_loader, 400)
Starting Training Loop... [0/400][0/29] Loss_D: 1.7484 Loss_G: 5.6300 D(x): 0.5497 D(G(z)): 0.5747 / 0.0057 [1/400][0/29] Loss_D: 0.0386 Loss_G: 12.8821 D(x): 0.9650 D(G(z)): 0.0000 / 0.0000
Traceback (most recent call last):
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
send_bytes(obj)
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
self._send_bytes(m[offset:offset + size])
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 411, in _send_bytes
self._send(header + buf)
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 368, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
Traceback (most recent call last):
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
send_bytes(obj)
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
self._send_bytes(m[offset:offset + size])
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 411, in _send_bytes
self._send(header + buf)
File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 368, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
--------------------------------------- KeyboardInterruptTraceback (most recent call last) <timed eval> in <module> ~/gan_plankton/src/models/models.py in train(self, dataloader, num_epochs) 162 # Calculate gradients for D in backward pass 163 errD_real.backward() --> 164 D_x = output.mean().item() 165 166 ## Train with all-fake batch KeyboardInterrupt:
Random Search¶
In [11]:
latent_size = 100
feature_map_size = 64
params_list = [{'beta': 0.5, 'lr': 0.002, 'num_epochs': 200},
{'beta': 0.5, 'lr': 0.02, 'num_epochs': 200},
{'beta': 0.5, 'lr': 0.0002, 'num_epochs': 200}]
In [13]:
%%time
i = 0
for params in params_list:
i += 1
print(f'\n------------------------\nAttempt {i}')
g = DCGAN_Generator(latent_size, feature_map_size, channel_size)
d = DCGAN_Discriminator(feature_map_size, channel_size)
gan = GAN(d, g, params['lr'], params['beta'])
gan.train(data_loader, params['num_epochs'])
plot_loss(gan.G_losses, gan.D_losses, img_path=f'../reports/model_analysis/loss_{i}.png')
generator_progress(gan.img_list, gif_path=f'../reports/model_analysis/progress_{i}.gif')
compare_fake_real(data_loader, gan.device, gan.img_list, img_path=f'../reports/model_analysis/comparison_{i}.png')
------------------------ Attempt 1 Starting Training Loop... [0/200][0/29] Loss_D: 2.2835 Loss_G: 32.6083 D(x): 0.3886 D(G(z)): 0.6013 / 0.0000 [1/200][0/29] Loss_D: 1.1055 Loss_G: 2.7054 D(x): 0.5974 D(G(z)): 0.1396 / 0.1766 [2/200][0/29] Loss_D: 1.9411 Loss_G: 1.3567 D(x): 0.5982 D(G(z)): 0.6294 / 0.3382 [3/200][0/29] Loss_D: 1.0989 Loss_G: 1.7607 D(x): 0.6011 D(G(z)): 0.3605 / 0.2048 [4/200][0/29] Loss_D: 1.1689 Loss_G: 1.3681 D(x): 0.6235 D(G(z)): 0.4219 / 0.3289 [5/200][0/29] Loss_D: 1.6864 Loss_G: 2.1163 D(x): 0.7363 D(G(z)): 0.5133 / 0.1300 [6/200][0/29] Loss_D: 1.1963 Loss_G: 1.8553 D(x): 0.6917 D(G(z)): 0.3842 / 0.2953 [7/200][0/29] Loss_D: 0.9443 Loss_G: 2.2620 D(x): 0.8552 D(G(z)): 0.4518 / 0.1799 [8/200][0/29] Loss_D: 0.8884 Loss_G: 4.3234 D(x): 0.8335 D(G(z)): 0.2097 / 0.0274 [9/200][0/29] Loss_D: 1.8353 Loss_G: 1.2328 D(x): 0.6178 D(G(z)): 0.4301 / 0.3527 [10/200][0/29] Loss_D: 1.4158 Loss_G: 2.9740 D(x): 0.7460 D(G(z)): 0.5850 / 0.1190 [11/200][0/29] Loss_D: 0.8684 Loss_G: 1.1933 D(x): 0.7271 D(G(z)): 0.3852 / 0.3558 [12/200][0/29] Loss_D: 1.6408 Loss_G: 5.7225 D(x): 0.7294 D(G(z)): 0.6215 / 0.0103 [13/200][0/29] Loss_D: 0.9872 Loss_G: 2.1780 D(x): 0.6806 D(G(z)): 0.3905 / 0.2347 [14/200][0/29] Loss_D: 1.7614 Loss_G: 3.0328 D(x): 0.6397 D(G(z)): 0.4790 / 0.0911 [15/200][0/29] Loss_D: 1.7219 Loss_G: 1.8334 D(x): 0.7582 D(G(z)): 0.4968 / 0.2134 [16/200][0/29] Loss_D: 0.6224 Loss_G: 2.4654 D(x): 0.7703 D(G(z)): 0.2799 / 0.1656 [17/200][0/29] Loss_D: 1.3724 Loss_G: 1.3972 D(x): 0.4445 D(G(z)): 0.1803 / 0.3516 [18/200][0/29] Loss_D: 1.5965 Loss_G: 1.6112 D(x): 0.5088 D(G(z)): 0.3901 / 0.2563 [19/200][0/29] Loss_D: 1.2428 Loss_G: 4.2019 D(x): 0.8719 D(G(z)): 0.5107 / 0.0413 [20/200][0/29] Loss_D: 1.3304 Loss_G: 0.4507 D(x): 0.3961 D(G(z)): 0.1865 / 0.6553 [21/200][0/29] Loss_D: 1.3969 Loss_G: 1.6007 D(x): 0.7412 D(G(z)): 0.5214 / 0.2519 [22/200][0/29] Loss_D: 1.5810 Loss_G: 2.1161 D(x): 0.9196 D(G(z)): 0.7304 / 0.1702 [23/200][0/29] Loss_D: 0.9821 Loss_G: 2.7262 D(x): 0.8028 D(G(z)): 0.4680 / 0.0948 [24/200][0/29] Loss_D: 0.7951 Loss_G: 2.7105 D(x): 0.7880 D(G(z)): 0.3744 / 0.1437 [25/200][0/29] Loss_D: 1.1901 Loss_G: 1.7959 D(x): 0.5550 D(G(z)): 0.2464 / 0.2036 [26/200][0/29] Loss_D: 0.7951 Loss_G: 4.0733 D(x): 0.6964 D(G(z)): 0.1901 / 0.0220 [27/200][0/29] Loss_D: 1.8314 Loss_G: 3.5780 D(x): 0.3648 D(G(z)): 0.2412 / 0.0641 [28/200][0/29] Loss_D: 1.8467 Loss_G: 3.0254 D(x): 0.6742 D(G(z)): 0.6759 / 0.0939 [29/200][0/29] Loss_D: 1.0094 Loss_G: 1.6438 D(x): 0.5764 D(G(z)): 0.2658 / 0.2394 [30/200][0/29] Loss_D: 0.9084 Loss_G: 1.4151 D(x): 0.5898 D(G(z)): 0.1890 / 0.3280 [31/200][0/29] Loss_D: 1.3075 Loss_G: 3.6923 D(x): 0.6858 D(G(z)): 0.5092 / 0.0628 [32/200][0/29] Loss_D: 0.9595 Loss_G: 1.2973 D(x): 0.5223 D(G(z)): 0.1547 / 0.3389 [33/200][0/29] Loss_D: 1.0841 Loss_G: 1.9989 D(x): 0.5727 D(G(z)): 0.2577 / 0.1757 [34/200][0/29] Loss_D: 1.1908 Loss_G: 3.0735 D(x): 0.9212 D(G(z)): 0.6022 / 0.0773 [35/200][0/29] Loss_D: 1.2716 Loss_G: 3.0411 D(x): 0.9360 D(G(z)): 0.6407 / 0.0649 [36/200][0/29] Loss_D: 1.1703 Loss_G: 1.4861 D(x): 0.4674 D(G(z)): 0.1953 / 0.3013 [37/200][0/29] Loss_D: 0.8977 Loss_G: 2.8588 D(x): 0.8424 D(G(z)): 0.4206 / 0.1277 [38/200][0/29] Loss_D: 0.7855 Loss_G: 2.6494 D(x): 0.6602 D(G(z)): 0.2604 / 0.1107 [39/200][0/29] Loss_D: 0.7063 Loss_G: 2.7175 D(x): 0.7222 D(G(z)): 0.2469 / 0.1246 [40/200][0/29] Loss_D: 1.2529 Loss_G: 0.6867 D(x): 0.5403 D(G(z)): 0.3915 / 0.5640 [41/200][0/29] Loss_D: 0.9757 Loss_G: 2.0904 D(x): 0.7189 D(G(z)): 0.4133 / 0.1540 [42/200][0/29] Loss_D: 1.6594 Loss_G: 4.2134 D(x): 0.9122 D(G(z)): 0.6735 / 0.0367 [43/200][0/29] Loss_D: 1.0452 Loss_G: 2.6355 D(x): 0.6350 D(G(z)): 0.3749 / 0.1029 [44/200][0/29] Loss_D: 0.7158 Loss_G: 1.8297 D(x): 0.7521 D(G(z)): 0.3159 / 0.1899 [45/200][0/29] Loss_D: 0.6936 Loss_G: 2.3368 D(x): 0.7646 D(G(z)): 0.2920 / 0.1282 [46/200][0/29] Loss_D: 0.8221 Loss_G: 1.7120 D(x): 0.6291 D(G(z)): 0.2094 / 0.2271 [47/200][0/29] Loss_D: 0.6562 Loss_G: 3.3522 D(x): 0.7885 D(G(z)): 0.2657 / 0.0579 [48/200][0/29] Loss_D: 0.9377 Loss_G: 2.4340 D(x): 0.7656 D(G(z)): 0.4246 / 0.1383 [49/200][0/29] Loss_D: 0.7840 Loss_G: 2.2770 D(x): 0.7443 D(G(z)): 0.3057 / 0.1393 [50/200][0/29] Loss_D: 0.9120 Loss_G: 1.2409 D(x): 0.5988 D(G(z)): 0.2436 / 0.3208 [51/200][0/29] Loss_D: 0.7616 Loss_G: 2.2756 D(x): 0.6827 D(G(z)): 0.2226 / 0.1388 [52/200][0/29] Loss_D: 0.9279 Loss_G: 1.3058 D(x): 0.5633 D(G(z)): 0.1874 / 0.3449 [53/200][0/29] Loss_D: 0.7933 Loss_G: 2.6349 D(x): 0.8672 D(G(z)): 0.4267 / 0.0976 [54/200][0/29] Loss_D: 1.4134 Loss_G: 1.8863 D(x): 0.7797 D(G(z)): 0.5985 / 0.2047 [55/200][0/29] Loss_D: 1.1985 Loss_G: 1.1663 D(x): 0.5198 D(G(z)): 0.2889 / 0.3882 [56/200][0/29] Loss_D: 0.8862 Loss_G: 1.8935 D(x): 0.6618 D(G(z)): 0.2749 / 0.2112 [57/200][0/29] Loss_D: 0.7507 Loss_G: 2.4137 D(x): 0.7243 D(G(z)): 0.2708 / 0.1185 [58/200][0/29] Loss_D: 0.9619 Loss_G: 2.9185 D(x): 0.6359 D(G(z)): 0.3225 / 0.0890 [59/200][0/29] Loss_D: 0.8766 Loss_G: 3.9035 D(x): 0.8979 D(G(z)): 0.4391 / 0.0355 [60/200][0/29] Loss_D: 0.5004 Loss_G: 2.6891 D(x): 0.7843 D(G(z)): 0.1800 / 0.1057 [61/200][0/29] Loss_D: 1.0449 Loss_G: 2.5086 D(x): 0.7916 D(G(z)): 0.4732 / 0.1202 [62/200][0/29] Loss_D: 0.7351 Loss_G: 2.3036 D(x): 0.7390 D(G(z)): 0.2913 / 0.1487 [63/200][0/29] Loss_D: 0.8934 Loss_G: 2.3340 D(x): 0.5453 D(G(z)): 0.1322 / 0.1951 [64/200][0/29] Loss_D: 1.0677 Loss_G: 3.0364 D(x): 0.6362 D(G(z)): 0.3603 / 0.0959 [65/200][0/29] Loss_D: 1.4400 Loss_G: 5.7303 D(x): 0.8967 D(G(z)): 0.6834 / 0.0081 [66/200][0/29] Loss_D: 0.4959 Loss_G: 4.5003 D(x): 0.9060 D(G(z)): 0.2920 / 0.0214 [67/200][0/29] Loss_D: 1.0404 Loss_G: 1.3085 D(x): 0.5111 D(G(z)): 0.1413 / 0.3247 [68/200][0/29] Loss_D: 0.8586 Loss_G: 3.1504 D(x): 0.7240 D(G(z)): 0.3560 / 0.0795 [69/200][0/29] Loss_D: 1.0339 Loss_G: 2.6222 D(x): 0.8395 D(G(z)): 0.4926 / 0.1245 [70/200][0/29] Loss_D: 0.7848 Loss_G: 2.8962 D(x): 0.5703 D(G(z)): 0.0509 / 0.0936 [71/200][0/29] Loss_D: 0.6850 Loss_G: 3.7088 D(x): 0.8033 D(G(z)): 0.3128 / 0.0457 [72/200][0/29] Loss_D: 0.6767 Loss_G: 2.7210 D(x): 0.8484 D(G(z)): 0.3236 / 0.1003 [73/200][0/29] Loss_D: 0.5061 Loss_G: 3.2974 D(x): 0.7967 D(G(z)): 0.1960 / 0.0610 [74/200][0/29] Loss_D: 0.7153 Loss_G: 3.4282 D(x): 0.8913 D(G(z)): 0.3672 / 0.0582 [75/200][0/29] Loss_D: 1.0084 Loss_G: 4.0326 D(x): 0.9229 D(G(z)): 0.4856 / 0.0306 [76/200][0/29] Loss_D: 1.4514 Loss_G: 1.2623 D(x): 0.3371 D(G(z)): 0.0848 / 0.3455 [77/200][0/29] Loss_D: 0.9571 Loss_G: 1.2713 D(x): 0.5316 D(G(z)): 0.1444 / 0.3819 [78/200][0/29] Loss_D: 1.1059 Loss_G: 2.7910 D(x): 0.8257 D(G(z)): 0.4941 / 0.0976 [79/200][0/29] Loss_D: 1.0345 Loss_G: 2.7013 D(x): 0.8334 D(G(z)): 0.5057 / 0.0976 [80/200][0/29] Loss_D: 1.0648 Loss_G: 1.9277 D(x): 0.4893 D(G(z)): 0.0787 / 0.2185 [81/200][0/29] Loss_D: 0.7226 Loss_G: 2.7720 D(x): 0.8200 D(G(z)): 0.3361 / 0.0931 [82/200][0/29] Loss_D: 0.8831 Loss_G: 4.1298 D(x): 0.8515 D(G(z)): 0.4504 / 0.0250 [83/200][0/29] Loss_D: 0.6630 Loss_G: 3.5263 D(x): 0.7766 D(G(z)): 0.2497 / 0.0673 [84/200][0/29] Loss_D: 1.0846 Loss_G: 2.5440 D(x): 0.6159 D(G(z)): 0.3510 / 0.1343 [85/200][0/29] Loss_D: 0.6645 Loss_G: 2.6756 D(x): 0.8603 D(G(z)): 0.3412 / 0.1082 [86/200][0/29] Loss_D: 1.3081 Loss_G: 2.7597 D(x): 0.7611 D(G(z)): 0.5619 / 0.1031 [87/200][0/29] Loss_D: 1.1930 Loss_G: 3.3565 D(x): 0.8764 D(G(z)): 0.5612 / 0.0869 [88/200][0/29] Loss_D: 0.6865 Loss_G: 2.5928 D(x): 0.7278 D(G(z)): 0.2437 / 0.1127 [89/200][0/29] Loss_D: 1.0425 Loss_G: 3.5137 D(x): 0.7278 D(G(z)): 0.4248 / 0.1043 [90/200][0/29] Loss_D: 0.7165 Loss_G: 2.2767 D(x): 0.6898 D(G(z)): 0.2388 / 0.1409 [91/200][0/29] Loss_D: 1.3840 Loss_G: 1.7983 D(x): 0.4362 D(G(z)): 0.2398 / 0.2566 [92/200][0/29] Loss_D: 0.6511 Loss_G: 3.8459 D(x): 0.9361 D(G(z)): 0.3975 / 0.0375 [93/200][0/29] Loss_D: 0.6403 Loss_G: 2.5490 D(x): 0.7834 D(G(z)): 0.2705 / 0.1246 [94/200][0/29] Loss_D: 0.9344 Loss_G: 2.3113 D(x): 0.4854 D(G(z)): 0.0689 / 0.1601 [95/200][0/29] Loss_D: 0.6840 Loss_G: 3.6685 D(x): 0.8232 D(G(z)): 0.3227 / 0.0550 [96/200][0/29] Loss_D: 1.6309 Loss_G: 3.2237 D(x): 0.8470 D(G(z)): 0.7041 / 0.0556 [97/200][0/29] Loss_D: 1.3938 Loss_G: 1.7663 D(x): 0.4442 D(G(z)): 0.3226 / 0.2370 [98/200][0/29] Loss_D: 1.4092 Loss_G: 1.8797 D(x): 0.3754 D(G(z)): 0.1760 / 0.2553 [99/200][0/29] Loss_D: 0.7321 Loss_G: 2.9709 D(x): 0.7543 D(G(z)): 0.2730 / 0.0850 [100/200][0/29] Loss_D: 0.9199 Loss_G: 3.6601 D(x): 0.7924 D(G(z)): 0.4143 / 0.0669 [101/200][0/29] Loss_D: 1.3423 Loss_G: 4.4336 D(x): 0.9455 D(G(z)): 0.6418 / 0.0289 [102/200][0/29] Loss_D: 0.6447 Loss_G: 2.9822 D(x): 0.7354 D(G(z)): 0.2080 / 0.1002 [103/200][0/29] Loss_D: 1.2139 Loss_G: 1.2188 D(x): 0.4532 D(G(z)): 0.1438 / 0.3747 [104/200][0/29] Loss_D: 0.8500 Loss_G: 2.2361 D(x): 0.6069 D(G(z)): 0.1712 / 0.1581 [105/200][0/29] Loss_D: 0.6991 Loss_G: 2.5403 D(x): 0.6482 D(G(z)): 0.1298 / 0.1300 [106/200][0/29] Loss_D: 1.5116 Loss_G: 1.6269 D(x): 0.3810 D(G(z)): 0.0756 / 0.2979 [107/200][0/29] Loss_D: 0.7589 Loss_G: 3.2101 D(x): 0.7651 D(G(z)): 0.3178 / 0.0706 [108/200][0/29] Loss_D: 0.4453 Loss_G: 3.5837 D(x): 0.8974 D(G(z)): 0.2484 / 0.0645 [109/200][0/29] Loss_D: 0.4369 Loss_G: 3.3941 D(x): 0.8592 D(G(z)): 0.2041 / 0.0630 [110/200][0/29] Loss_D: 0.7835 Loss_G: 2.9566 D(x): 0.6184 D(G(z)): 0.0999 / 0.1160 [111/200][0/29] Loss_D: 0.4426 Loss_G: 4.0989 D(x): 0.8629 D(G(z)): 0.1848 / 0.0544 [112/200][0/29] Loss_D: 0.7267 Loss_G: 4.7461 D(x): 0.8487 D(G(z)): 0.3532 / 0.0249 [113/200][0/29] Loss_D: 0.5442 Loss_G: 3.9678 D(x): 0.8849 D(G(z)): 0.2849 / 0.0418 [114/200][0/29] Loss_D: 0.6656 Loss_G: 3.8949 D(x): 0.6899 D(G(z)): 0.0723 / 0.0489 [115/200][0/29] Loss_D: 0.5659 Loss_G: 3.6755 D(x): 0.8755 D(G(z)): 0.2892 / 0.0629 [116/200][0/29] Loss_D: 0.8313 Loss_G: 5.1413 D(x): 0.8806 D(G(z)): 0.4035 / 0.0294 [117/200][0/29] Loss_D: 0.7564 Loss_G: 5.0260 D(x): 0.9516 D(G(z)): 0.4335 / 0.0145 [118/200][0/29] Loss_D: 0.6581 Loss_G: 3.2246 D(x): 0.6838 D(G(z)): 0.1664 / 0.0824 [119/200][0/29] Loss_D: 1.0017 Loss_G: 2.2499 D(x): 0.5614 D(G(z)): 0.1789 / 0.2237 [120/200][0/29] Loss_D: 0.3008 Loss_G: 3.7065 D(x): 0.8900 D(G(z)): 0.1340 / 0.0497 [121/200][0/29] Loss_D: 0.6021 Loss_G: 3.5369 D(x): 0.7660 D(G(z)): 0.2107 / 0.0557 [122/200][0/29] Loss_D: 0.6421 Loss_G: 6.3897 D(x): 0.9749 D(G(z)): 0.3953 / 0.0043 [123/200][0/29] Loss_D: 0.5960 Loss_G: 3.4962 D(x): 0.7834 D(G(z)): 0.2240 / 0.0728 [124/200][0/29] Loss_D: 0.7310 Loss_G: 3.7728 D(x): 0.7508 D(G(z)): 0.2735 / 0.0522 [125/200][0/29] Loss_D: 0.6630 Loss_G: 5.9239 D(x): 0.9363 D(G(z)): 0.3697 / 0.0098 [126/200][0/29] Loss_D: 0.5144 Loss_G: 3.5854 D(x): 0.7760 D(G(z)): 0.1505 / 0.0838 [127/200][0/29] Loss_D: 0.3239 Loss_G: 3.3105 D(x): 0.8988 D(G(z)): 0.1636 / 0.0636 [128/200][0/29] Loss_D: 1.3965 Loss_G: 7.7227 D(x): 0.9558 D(G(z)): 0.5548 / 0.0031 [129/200][0/29] Loss_D: 0.7096 Loss_G: 5.0027 D(x): 0.8784 D(G(z)): 0.3355 / 0.0219 [130/200][0/29] Loss_D: 0.4417 Loss_G: 2.8963 D(x): 0.7734 D(G(z)): 0.1177 / 0.1092 [131/200][0/29] Loss_D: 0.4894 Loss_G: 5.2318 D(x): 0.9567 D(G(z)): 0.2912 / 0.0141 [132/200][0/29] Loss_D: 0.3637 Loss_G: 3.5786 D(x): 0.8455 D(G(z)): 0.1354 / 0.0743 [133/200][0/29] Loss_D: 0.8824 Loss_G: 3.1853 D(x): 0.5647 D(G(z)): 0.0360 / 0.1539 [134/200][0/29] Loss_D: 0.2684 Loss_G: 4.7922 D(x): 0.9368 D(G(z)): 0.1561 / 0.0215 [135/200][0/29] Loss_D: 0.5843 Loss_G: 2.6569 D(x): 0.6995 D(G(z)): 0.0877 / 0.1396 [136/200][0/29] Loss_D: 0.5624 Loss_G: 6.5969 D(x): 0.9102 D(G(z)): 0.3120 / 0.0066 [137/200][0/29] Loss_D: 0.4171 Loss_G: 4.2252 D(x): 0.8153 D(G(z)): 0.1401 / 0.0439 [138/200][0/29] Loss_D: 0.5241 Loss_G: 4.7796 D(x): 0.9119 D(G(z)): 0.2764 / 0.0191 [139/200][0/29] Loss_D: 0.3959 Loss_G: 5.8250 D(x): 0.9599 D(G(z)): 0.2508 / 0.0083 [140/200][0/29] Loss_D: 0.6832 Loss_G: 3.6222 D(x): 0.6162 D(G(z)): 0.0516 / 0.1126 [141/200][0/29] Loss_D: 0.4718 Loss_G: 4.3679 D(x): 0.8262 D(G(z)): 0.1721 / 0.0355 [142/200][0/29] Loss_D: 0.8003 Loss_G: 3.1882 D(x): 0.5807 D(G(z)): 0.0446 / 0.1294 [143/200][0/29] Loss_D: 0.2672 Loss_G: 5.9478 D(x): 0.9543 D(G(z)): 0.1483 / 0.0081 [144/200][0/29] Loss_D: 0.3440 Loss_G: 6.7679 D(x): 0.9360 D(G(z)): 0.1978 / 0.0076 [145/200][0/29] Loss_D: 0.5623 Loss_G: 5.3605 D(x): 0.9274 D(G(z)): 0.2840 / 0.0283 [146/200][0/29] Loss_D: 0.4908 Loss_G: 5.7591 D(x): 0.8781 D(G(z)): 0.2232 / 0.0289 [147/200][0/29] Loss_D: 0.5562 Loss_G: 3.9890 D(x): 0.7267 D(G(z)): 0.0561 / 0.0785 [148/200][0/29] Loss_D: 0.4357 Loss_G: 5.6167 D(x): 0.9425 D(G(z)): 0.2550 / 0.0142 [149/200][0/29] Loss_D: 0.4790 Loss_G: 4.8127 D(x): 0.7428 D(G(z)): 0.0569 / 0.0542 [150/200][0/29] Loss_D: 0.3507 Loss_G: 4.8229 D(x): 0.8887 D(G(z)): 0.1499 / 0.0295 [151/200][0/29] Loss_D: 0.3991 Loss_G: 8.0777 D(x): 0.9837 D(G(z)): 0.2293 / 0.0015 [152/200][0/29] Loss_D: 0.3773 Loss_G: 3.5874 D(x): 0.7974 D(G(z)): 0.0787 / 0.0947 [153/200][0/29] Loss_D: 0.7683 Loss_G: 5.4596 D(x): 0.9371 D(G(z)): 0.3716 / 0.0130 [154/200][0/29] Loss_D: 0.3042 Loss_G: 5.7152 D(x): 0.9465 D(G(z)): 0.1651 / 0.0183 [155/200][0/29] Loss_D: 0.4589 Loss_G: 6.0056 D(x): 0.9725 D(G(z)): 0.2587 / 0.0116 [156/200][0/29] Loss_D: 0.2999 Loss_G: 4.6272 D(x): 0.8969 D(G(z)): 0.1324 / 0.0345 [157/200][0/29] Loss_D: 0.1402 Loss_G: 4.3471 D(x): 0.9450 D(G(z)): 0.0666 / 0.0382 [158/200][0/29] Loss_D: 1.1770 Loss_G: 10.5333 D(x): 0.9764 D(G(z)): 0.5582 / 0.0013 [159/200][0/29] Loss_D: 0.4860 Loss_G: 4.6450 D(x): 0.7963 D(G(z)): 0.1385 / 0.0402 [160/200][0/29] Loss_D: 0.2349 Loss_G: 6.6266 D(x): 0.9716 D(G(z)): 0.1528 / 0.0043 [161/200][0/29] Loss_D: 0.1961 Loss_G: 5.9084 D(x): 0.8510 D(G(z)): 0.0073 / 0.0087 [162/200][0/29] Loss_D: 0.2908 Loss_G: 4.8945 D(x): 0.9449 D(G(z)): 0.1520 / 0.0248 [163/200][0/29] Loss_D: 0.4272 Loss_G: 5.6258 D(x): 0.9583 D(G(z)): 0.2375 / 0.0124 [164/200][0/29] Loss_D: 0.2180 Loss_G: 5.3437 D(x): 0.9436 D(G(z)): 0.1156 / 0.0181 [165/200][0/29] Loss_D: 0.6480 Loss_G: 7.4951 D(x): 0.9556 D(G(z)): 0.3533 / 0.0031 [166/200][0/29] Loss_D: 0.3351 Loss_G: 5.3655 D(x): 0.8045 D(G(z)): 0.0317 / 0.0271 [167/200][0/29] Loss_D: 0.2607 Loss_G: 6.5938 D(x): 0.9579 D(G(z)): 0.1239 / 0.0076 [168/200][0/29] Loss_D: 0.3751 Loss_G: 5.1330 D(x): 0.8624 D(G(z)): 0.1254 / 0.0257 [169/200][0/29] Loss_D: 0.3456 Loss_G: 6.5348 D(x): 0.9572 D(G(z)): 0.1699 / 0.0082 [170/200][0/29] Loss_D: 0.0851 Loss_G: 6.1280 D(x): 0.9677 D(G(z)): 0.0443 / 0.0083 [171/200][0/29] Loss_D: 0.2036 Loss_G: 5.8067 D(x): 0.9516 D(G(z)): 0.0942 / 0.0100 [172/200][0/29] Loss_D: 0.2516 Loss_G: 5.7609 D(x): 0.8945 D(G(z)): 0.0749 / 0.0180 [173/200][0/29] Loss_D: 1.1331 Loss_G: 8.5417 D(x): 0.9745 D(G(z)): 0.4362 / 0.0210 [174/200][0/29] Loss_D: 0.2578 Loss_G: 5.8318 D(x): 0.9186 D(G(z)): 0.1041 / 0.0228 [175/200][0/29] Loss_D: 0.2192 Loss_G: 4.3903 D(x): 0.8752 D(G(z)): 0.0518 / 0.0800 [176/200][0/29] Loss_D: 0.1451 Loss_G: 5.1527 D(x): 0.9419 D(G(z)): 0.0606 / 0.0205 [177/200][0/29] Loss_D: 0.1349 Loss_G: 5.9880 D(x): 0.9668 D(G(z)): 0.0771 / 0.0138 [178/200][0/29] Loss_D: 0.1169 Loss_G: 6.7450 D(x): 0.9545 D(G(z)): 0.0474 / 0.0061 [179/200][0/29] Loss_D: 0.1777 Loss_G: 5.0037 D(x): 0.9259 D(G(z)): 0.0657 / 0.0225 [180/200][0/29] Loss_D: 0.3729 Loss_G: 8.8704 D(x): 0.9756 D(G(z)): 0.1991 / 0.0025 [181/200][0/29] Loss_D: 0.7234 Loss_G: 3.8527 D(x): 0.7000 D(G(z)): 0.0727 / 0.1494 [182/200][0/29] Loss_D: 0.2349 Loss_G: 5.5558 D(x): 0.9555 D(G(z)): 0.1236 / 0.0196 [183/200][0/29] Loss_D: 0.2982 Loss_G: 6.2308 D(x): 0.8985 D(G(z)): 0.1047 / 0.0139 [184/200][0/29] Loss_D: 0.1981 Loss_G: 6.9236 D(x): 0.9598 D(G(z)): 0.0999 / 0.0069 [185/200][0/29] Loss_D: 0.1359 Loss_G: 6.3599 D(x): 0.9477 D(G(z)): 0.0640 / 0.0071 [186/200][0/29] Loss_D: 0.0985 Loss_G: 5.7110 D(x): 0.9538 D(G(z)): 0.0391 / 0.0116 [187/200][0/29] Loss_D: 1.4528 Loss_G: 11.0654 D(x): 0.9699 D(G(z)): 0.5705 / 0.0002 [188/200][0/29] Loss_D: 0.3667 Loss_G: 5.5523 D(x): 0.8457 D(G(z)): 0.0974 / 0.0274 [189/200][0/29] Loss_D: 0.2580 Loss_G: 4.8627 D(x): 0.8392 D(G(z)): 0.0309 / 0.0784 [190/200][0/29] Loss_D: 0.0608 Loss_G: 5.1869 D(x): 0.9773 D(G(z)): 0.0293 / 0.0322 [191/200][0/29] Loss_D: 0.0680 Loss_G: 5.9197 D(x): 0.9823 D(G(z)): 0.0412 / 0.0091 [192/200][0/29] Loss_D: 0.2669 Loss_G: 8.0872 D(x): 0.9357 D(G(z)): 0.1133 / 0.0086 [193/200][0/29] Loss_D: 0.0725 Loss_G: 6.6767 D(x): 0.9595 D(G(z)): 0.0256 / 0.0093 [194/200][0/29] Loss_D: 0.8029 Loss_G: 4.8991 D(x): 0.6601 D(G(z)): 0.0500 / 0.1268 [195/200][0/29] Loss_D: 0.3127 Loss_G: 5.0263 D(x): 0.8920 D(G(z)): 0.1058 / 0.0412 [196/200][0/29] Loss_D: 0.0779 Loss_G: 7.8588 D(x): 0.9510 D(G(z)): 0.0208 / 0.0032 [197/200][0/29] Loss_D: 0.1735 Loss_G: 6.8080 D(x): 0.9699 D(G(z)): 0.1109 / 0.0043 [198/200][0/29] Loss_D: 0.2196 Loss_G: 8.8235 D(x): 0.9769 D(G(z)): 0.1421 / 0.0029 [199/200][0/29] Loss_D: 0.5030 Loss_G: 9.8965 D(x): 0.9959 D(G(z)): 0.2848 / 0.0007
------------------------ Attempt 2 Starting Training Loop... [0/200][0/29] Loss_D: 1.9751 Loss_G: 66.9294 D(x): 0.6796 D(G(z)): 0.7195 / 0.0000 [1/200][0/29] Loss_D: 12.4003 Loss_G: 4.1059 D(x): 0.9989 D(G(z)): 0.9637 / 0.3935 [2/200][0/29] Loss_D: 4.2711 Loss_G: 2.0941 D(x): 0.3736 D(G(z)): 0.3233 / 0.2882 [3/200][0/29] Loss_D: 3.7410 Loss_G: 3.4606 D(x): 0.7599 D(G(z)): 0.1623 / 0.1589 [4/200][0/29] Loss_D: 1.7545 Loss_G: 5.4449 D(x): 0.8846 D(G(z)): 0.4961 / 0.0543 [5/200][0/29] Loss_D: 3.0204 Loss_G: 0.7881 D(x): 0.8065 D(G(z)): 0.7084 / 0.6231 [6/200][0/29] Loss_D: 1.5088 Loss_G: 2.0297 D(x): 0.6164 D(G(z)): 0.5791 / 0.1723 [7/200][0/29] Loss_D: 0.8893 Loss_G: 3.8600 D(x): 0.7649 D(G(z)): 0.3564 / 0.0800 [8/200][0/29] Loss_D: 1.7827 Loss_G: 9.2070 D(x): 0.9904 D(G(z)): 0.6952 / 0.0003 [9/200][0/29] Loss_D: 0.1977 Loss_G: 4.0662 D(x): 0.9214 D(G(z)): 0.0734 / 0.0342 [10/200][0/29] Loss_D: 1.3023 Loss_G: 7.6643 D(x): 0.8539 D(G(z)): 0.3017 / 0.0263 [11/200][0/29] Loss_D: 0.3778 Loss_G: 3.2351 D(x): 0.8637 D(G(z)): 0.1009 / 0.0759 [12/200][0/29] Loss_D: 0.1858 Loss_G: 4.8647 D(x): 0.9720 D(G(z)): 0.0636 / 0.0109 [13/200][0/29] Loss_D: 0.1443 Loss_G: 5.4427 D(x): 0.9553 D(G(z)): 0.0818 / 0.0252 [14/200][0/29] Loss_D: 0.1471 Loss_G: 6.8168 D(x): 0.9749 D(G(z)): 0.0671 / 0.0025 [15/200][0/29] Loss_D: 0.3722 Loss_G: 3.9049 D(x): 0.9173 D(G(z)): 0.1273 / 0.0334 [16/200][0/29] Loss_D: 0.7778 Loss_G: 9.3606 D(x): 0.9711 D(G(z)): 0.3316 / 0.0002 [17/200][0/29] Loss_D: 0.1253 Loss_G: 4.0437 D(x): 0.9615 D(G(z)): 0.0787 / 0.0288 [18/200][0/29] Loss_D: 0.9352 Loss_G: 6.1071 D(x): 0.6736 D(G(z)): 0.3531 / 0.0047 [19/200][0/29] Loss_D: 0.3447 Loss_G: 2.6794 D(x): 0.7774 D(G(z)): 0.0597 / 0.1193 [20/200][0/29] Loss_D: 1.2714 Loss_G: 2.0375 D(x): 0.6321 D(G(z)): 0.5039 / 0.1716 [21/200][0/29] Loss_D: 0.9496 Loss_G: 1.2845 D(x): 0.5206 D(G(z)): 0.2018 / 0.3061 [22/200][0/29] Loss_D: 3.5147 Loss_G: 0.4028 D(x): 0.0712 D(G(z)): 0.0410 / 0.7370 [23/200][0/29] Loss_D: 0.1195 Loss_G: 3.6513 D(x): 0.9715 D(G(z)): 0.0821 / 0.0342 [24/200][0/29] Loss_D: 1.2757 Loss_G: 1.8618 D(x): 0.8450 D(G(z)): 0.6559 / 0.2242 [25/200][0/29] Loss_D: 1.1837 Loss_G: 1.3958 D(x): 0.7344 D(G(z)): 0.4527 / 0.3437 [26/200][0/29] Loss_D: 2.5104 Loss_G: 0.4725 D(x): 0.1210 D(G(z)): 0.0910 / 0.6974 [27/200][0/29] Loss_D: 4.3261 Loss_G: 0.9872 D(x): 0.0246 D(G(z)): 0.0024 / 0.4412 [28/200][0/29] Loss_D: 0.5520 Loss_G: 3.2382 D(x): 0.7241 D(G(z)): 0.1671 / 0.0549 [29/200][0/29] Loss_D: 0.8382 Loss_G: 3.4740 D(x): 0.7140 D(G(z)): 0.3450 / 0.0509 [30/200][0/29] Loss_D: 0.1134 Loss_G: 3.6497 D(x): 0.9227 D(G(z)): 0.0276 / 0.0316 [31/200][0/29] Loss_D: 0.5286 Loss_G: 2.9533 D(x): 0.7133 D(G(z)): 0.1007 / 0.0802 [32/200][0/29] Loss_D: 1.1673 Loss_G: 1.9769 D(x): 0.6430 D(G(z)): 0.4484 / 0.1745 [33/200][0/29] Loss_D: 1.1257 Loss_G: 4.4701 D(x): 0.6837 D(G(z)): 0.4738 / 0.0175 [34/200][0/29] Loss_D: 0.4865 Loss_G: 3.9086 D(x): 0.8557 D(G(z)): 0.2604 / 0.0313 [35/200][0/29] Loss_D: 0.1825 Loss_G: 11.8989 D(x): 0.8450 D(G(z)): 0.0000 / 0.0000 [36/200][0/29] Loss_D: 1.7943 Loss_G: 8.1102 D(x): 0.9864 D(G(z)): 0.7640 / 0.0014 [37/200][0/29] Loss_D: 0.7102 Loss_G: 2.7275 D(x): 0.6597 D(G(z)): 0.1875 / 0.0993 [38/200][0/29] Loss_D: 0.6252 Loss_G: 1.5846 D(x): 0.7234 D(G(z)): 0.2332 / 0.2338 [39/200][0/29] Loss_D: 1.5515 Loss_G: 2.1904 D(x): 0.6970 D(G(z)): 0.6271 / 0.1457 [40/200][0/29] Loss_D: 0.7121 Loss_G: 2.3850 D(x): 0.7725 D(G(z)): 0.3058 / 0.1146 [41/200][0/29] Loss_D: 0.2174 Loss_G: 3.3182 D(x): 0.9421 D(G(z)): 0.1419 / 0.0518 [42/200][0/29] Loss_D: 0.7926 Loss_G: 2.0873 D(x): 0.7978 D(G(z)): 0.3885 / 0.1617 [43/200][0/29] Loss_D: 1.1600 Loss_G: 1.2720 D(x): 0.7434 D(G(z)): 0.5040 / 0.3112 [44/200][0/29] Loss_D: 0.6400 Loss_G: 2.1894 D(x): 0.7682 D(G(z)): 0.2820 / 0.1347 [45/200][0/29] Loss_D: 1.7690 Loss_G: 1.9007 D(x): 0.4585 D(G(z)): 0.5386 / 0.2088 [46/200][0/29] Loss_D: 1.0505 Loss_G: 1.3561 D(x): 0.5862 D(G(z)): 0.3436 / 0.2977 [47/200][0/29] Loss_D: 0.8909 Loss_G: 2.6219 D(x): 0.7931 D(G(z)): 0.4205 / 0.0988 [48/200][0/29] Loss_D: 1.5150 Loss_G: 1.8983 D(x): 0.6782 D(G(z)): 0.6094 / 0.1914 [49/200][0/29] Loss_D: 1.1042 Loss_G: 0.9211 D(x): 0.4363 D(G(z)): 0.1233 / 0.5288 [50/200][0/29] Loss_D: 1.2323 Loss_G: 4.0912 D(x): 0.7409 D(G(z)): 0.5085 / 0.0281 [51/200][0/29] Loss_D: 1.5655 Loss_G: 1.5757 D(x): 0.7451 D(G(z)): 0.6942 / 0.2220 [52/200][0/29] Loss_D: 1.3916 Loss_G: 1.0321 D(x): 0.3676 D(G(z)): 0.2203 / 0.4006 [53/200][0/29] Loss_D: 0.8159 Loss_G: 2.2653 D(x): 0.7938 D(G(z)): 0.4005 / 0.1328 [54/200][0/29] Loss_D: 1.0106 Loss_G: 2.1008 D(x): 0.6384 D(G(z)): 0.3703 / 0.1509 [55/200][0/29] Loss_D: 3.7504 Loss_G: 1.0445 D(x): 0.0548 D(G(z)): 0.0364 / 0.3810 [56/200][0/29] Loss_D: 6.3292 Loss_G: 1.0883 D(x): 0.0219 D(G(z)): 0.0023 / 0.3679 [57/200][0/29] Loss_D: 1.2598 Loss_G: 0.7870 D(x): 0.4665 D(G(z)): 0.2967 / 0.4933 [58/200][0/29] Loss_D: 3.6375 Loss_G: 1.7850 D(x): 0.0464 D(G(z)): 0.0360 / 0.2104 [59/200][0/29] Loss_D: 1.2446 Loss_G: 1.6762 D(x): 0.4290 D(G(z)): 0.2432 / 0.2213 [60/200][0/29] Loss_D: 0.6053 Loss_G: 2.1331 D(x): 0.7200 D(G(z)): 0.2093 / 0.1578 [61/200][0/29] Loss_D: 1.5043 Loss_G: 3.4930 D(x): 0.3065 D(G(z)): 0.0043 / 0.0510 [62/200][0/29] Loss_D: 0.4903 Loss_G: 2.5064 D(x): 0.7846 D(G(z)): 0.1754 / 0.1084 [63/200][0/29] Loss_D: 2.5199 Loss_G: 1.0204 D(x): 0.1366 D(G(z)): 0.0800 / 0.4149 [64/200][0/29] Loss_D: 2.1323 Loss_G: 1.7136 D(x): 0.2006 D(G(z)): 0.0505 / 0.2061 [65/200][0/29] Loss_D: 3.2178 Loss_G: 5.0639 D(x): 0.9618 D(G(z)): 0.9206 / 0.0099 [66/200][0/29] Loss_D: 1.2994 Loss_G: 1.5619 D(x): 0.5545 D(G(z)): 0.4403 / 0.2557 [67/200][0/29] Loss_D: 1.0362 Loss_G: 5.3062 D(x): 0.9437 D(G(z)): 0.5484 / 0.0076 [68/200][0/29] Loss_D: 1.8644 Loss_G: 4.7128 D(x): 0.8728 D(G(z)): 0.7468 / 0.0226 [69/200][0/29] Loss_D: 0.6863 Loss_G: 4.3588 D(x): 0.9104 D(G(z)): 0.4186 / 0.0186 [70/200][0/29] Loss_D: 1.3299 Loss_G: 0.6582 D(x): 0.3401 D(G(z)): 0.1249 / 0.5643 [71/200][0/29] Loss_D: 0.8472 Loss_G: 1.7364 D(x): 0.6978 D(G(z)): 0.3395 / 0.2120 [72/200][0/29] Loss_D: 0.8239 Loss_G: 2.1738 D(x): 0.9199 D(G(z)): 0.4826 / 0.1318 [73/200][0/29] Loss_D: 1.1450 Loss_G: 2.0642 D(x): 0.6945 D(G(z)): 0.4777 / 0.1828 [74/200][0/29] Loss_D: 0.9250 Loss_G: 2.1558 D(x): 0.6223 D(G(z)): 0.3001 / 0.1646 [75/200][0/29] Loss_D: 0.6380 Loss_G: 2.3583 D(x): 0.7780 D(G(z)): 0.2536 / 0.1437 [76/200][0/29] Loss_D: 1.1466 Loss_G: 1.5917 D(x): 0.6028 D(G(z)): 0.4066 / 0.2480 [77/200][0/29] Loss_D: 0.7577 Loss_G: 1.6612 D(x): 0.6816 D(G(z)): 0.2360 / 0.2292 [78/200][0/29] Loss_D: 1.3601 Loss_G: 2.1586 D(x): 0.8163 D(G(z)): 0.6346 / 0.1342 [79/200][0/29] Loss_D: 1.1372 Loss_G: 2.5334 D(x): 0.8929 D(G(z)): 0.5853 / 0.1269 [80/200][0/29] Loss_D: 1.4100 Loss_G: 0.7339 D(x): 0.3450 D(G(z)): 0.1676 / 0.5182 [81/200][0/29] Loss_D: 0.9886 Loss_G: 2.1326 D(x): 0.7128 D(G(z)): 0.4331 / 0.1480 [82/200][0/29] Loss_D: 0.9781 Loss_G: 1.1715 D(x): 0.5617 D(G(z)): 0.2669 / 0.3595 [83/200][0/29] Loss_D: 1.2283 Loss_G: 3.3048 D(x): 0.6553 D(G(z)): 0.4407 / 0.0866 [84/200][0/29] Loss_D: 1.2110 Loss_G: 2.3655 D(x): 0.9310 D(G(z)): 0.6161 / 0.1154 [85/200][0/29] Loss_D: 1.0434 Loss_G: 1.3979 D(x): 0.7324 D(G(z)): 0.4756 / 0.2798 [86/200][0/29] Loss_D: 2.1377 Loss_G: 1.4938 D(x): 0.8877 D(G(z)): 0.8306 / 0.2431 [87/200][0/29] Loss_D: 0.9628 Loss_G: 3.7818 D(x): 0.8510 D(G(z)): 0.4757 / 0.0372 [88/200][0/29] Loss_D: 0.9212 Loss_G: 2.1103 D(x): 0.6238 D(G(z)): 0.2802 / 0.1530 [89/200][0/29] Loss_D: 0.9740 Loss_G: 2.3410 D(x): 0.7150 D(G(z)): 0.4255 / 0.1313 [90/200][0/29] Loss_D: 1.0540 Loss_G: 1.6536 D(x): 0.6025 D(G(z)): 0.3860 / 0.2537 [91/200][0/29] Loss_D: 0.8323 Loss_G: 3.1127 D(x): 0.8360 D(G(z)): 0.4317 / 0.0577 [92/200][0/29] Loss_D: 0.9024 Loss_G: 1.7149 D(x): 0.5336 D(G(z)): 0.1227 / 0.2325 [93/200][0/29] Loss_D: 1.1715 Loss_G: 1.4415 D(x): 0.4747 D(G(z)): 0.2145 / 0.3197 [94/200][0/29] Loss_D: 1.2983 Loss_G: 1.1546 D(x): 0.4676 D(G(z)): 0.3313 / 0.4036 [95/200][0/29] Loss_D: 0.5449 Loss_G: 4.2465 D(x): 0.7712 D(G(z)): 0.1987 / 0.0216 [96/200][0/29] Loss_D: 1.3461 Loss_G: 1.7545 D(x): 0.4359 D(G(z)): 0.2541 / 0.2134 [97/200][0/29] Loss_D: 2.0263 Loss_G: 1.3461 D(x): 0.2284 D(G(z)): 0.0966 / 0.3087 [98/200][0/29] Loss_D: 0.7035 Loss_G: 2.6059 D(x): 0.7613 D(G(z)): 0.2990 / 0.0995 [99/200][0/29] Loss_D: 0.6885 Loss_G: 2.5773 D(x): 0.6041 D(G(z)): 0.0897 / 0.0980 [100/200][0/29] Loss_D: 1.0293 Loss_G: 0.8833 D(x): 0.6819 D(G(z)): 0.4282 / 0.4626 [101/200][0/29] Loss_D: 0.2618 Loss_G: 4.6638 D(x): 0.8991 D(G(z)): 0.1340 / 0.0161 [102/200][0/29] Loss_D: 0.7861 Loss_G: 4.8881 D(x): 0.9885 D(G(z)): 0.4847 / 0.0179 [103/200][0/29] Loss_D: 0.1283 Loss_G: 4.0953 D(x): 0.9895 D(G(z)): 0.1058 / 0.0282 [104/200][0/29] Loss_D: 1.0306 Loss_G: 4.6046 D(x): 0.8479 D(G(z)): 0.5019 / 0.0331 [105/200][0/29] Loss_D: 0.9800 Loss_G: 3.5188 D(x): 0.8921 D(G(z)): 0.5129 / 0.0495 [106/200][0/29] Loss_D: 1.3450 Loss_G: 3.4180 D(x): 0.6076 D(G(z)): 0.4647 / 0.0499 [107/200][0/29] Loss_D: 0.9966 Loss_G: 4.0362 D(x): 0.7838 D(G(z)): 0.4277 / 0.0408 [108/200][0/29] Loss_D: 1.2124 Loss_G: 1.8489 D(x): 0.8421 D(G(z)): 0.5850 / 0.2121 [109/200][0/29] Loss_D: 0.8413 Loss_G: 3.2374 D(x): 0.8661 D(G(z)): 0.4466 / 0.0576 [110/200][0/29] Loss_D: 0.7904 Loss_G: 2.8670 D(x): 0.7016 D(G(z)): 0.2574 / 0.0874 [111/200][0/29] Loss_D: 1.0701 Loss_G: 2.1187 D(x): 0.6490 D(G(z)): 0.3206 / 0.1639 [112/200][0/29] Loss_D: 1.2260 Loss_G: 2.6678 D(x): 0.6022 D(G(z)): 0.4170 / 0.1119 [113/200][0/29] Loss_D: 1.1024 Loss_G: 1.4701 D(x): 0.4625 D(G(z)): 0.1577 / 0.3462 [114/200][0/29] Loss_D: 0.8550 Loss_G: 1.8601 D(x): 0.6268 D(G(z)): 0.2498 / 0.2020 [115/200][0/29] Loss_D: 0.7888 Loss_G: 1.2031 D(x): 0.5789 D(G(z)): 0.1100 / 0.4392 [116/200][0/29] Loss_D: 0.7083 Loss_G: 3.8584 D(x): 0.8921 D(G(z)): 0.4049 / 0.0474 [117/200][0/29] Loss_D: 0.7887 Loss_G: 3.3678 D(x): 0.7331 D(G(z)): 0.3039 / 0.0561 [118/200][0/29] Loss_D: 2.2271 Loss_G: 6.2371 D(x): 0.9385 D(G(z)): 0.7683 / 0.0031 [119/200][0/29] Loss_D: 0.6425 Loss_G: 5.0002 D(x): 0.8451 D(G(z)): 0.3116 / 0.0155 [120/200][0/29] Loss_D: 0.6774 Loss_G: 2.6313 D(x): 0.6092 D(G(z)): 0.0582 / 0.1258 [121/200][0/29] Loss_D: 1.3281 Loss_G: 4.1112 D(x): 0.9362 D(G(z)): 0.6122 / 0.0329 [122/200][0/29] Loss_D: 1.0105 Loss_G: 3.1506 D(x): 0.7359 D(G(z)): 0.4094 / 0.0795 [123/200][0/29] Loss_D: 0.6934 Loss_G: 4.5640 D(x): 0.7838 D(G(z)): 0.2984 / 0.0249 [124/200][0/29] Loss_D: 0.9052 Loss_G: 2.5698 D(x): 0.5742 D(G(z)): 0.1455 / 0.1761 [125/200][0/29] Loss_D: 1.2705 Loss_G: 4.1997 D(x): 0.9035 D(G(z)): 0.5955 / 0.0317 [126/200][0/29] Loss_D: 0.6749 Loss_G: 4.2474 D(x): 0.9088 D(G(z)): 0.3806 / 0.0230 [127/200][0/29] Loss_D: 1.0536 Loss_G: 3.3855 D(x): 0.9487 D(G(z)): 0.5260 / 0.0997 [128/200][0/29] Loss_D: 0.5631 Loss_G: 3.0384 D(x): 0.7617 D(G(z)): 0.1810 / 0.1079 [129/200][0/29] Loss_D: 0.7303 Loss_G: 3.6942 D(x): 0.7838 D(G(z)): 0.2924 / 0.0491 [130/200][0/29] Loss_D: 0.5387 Loss_G: 3.7396 D(x): 0.8623 D(G(z)): 0.2519 / 0.0400 [131/200][0/29] Loss_D: 0.7680 Loss_G: 2.8684 D(x): 0.6691 D(G(z)): 0.1948 / 0.1184 [132/200][0/29] Loss_D: 0.3215 Loss_G: 3.9116 D(x): 0.8101 D(G(z)): 0.0297 / 0.0411 [133/200][0/29] Loss_D: 1.4394 Loss_G: 7.0205 D(x): 0.9618 D(G(z)): 0.6531 / 0.0021 [134/200][0/29] Loss_D: 0.8761 Loss_G: 4.0286 D(x): 0.9604 D(G(z)): 0.4676 / 0.0467 [135/200][0/29] Loss_D: 0.4350 Loss_G: 3.1027 D(x): 0.7932 D(G(z)): 0.1429 / 0.0930 [136/200][0/29] Loss_D: 0.3152 Loss_G: 3.1488 D(x): 0.8289 D(G(z)): 0.0871 / 0.0724 [137/200][0/29] Loss_D: 1.1232 Loss_G: 6.6052 D(x): 0.9348 D(G(z)): 0.5291 / 0.0046 [138/200][0/29] Loss_D: 0.7551 Loss_G: 2.7692 D(x): 0.6429 D(G(z)): 0.0419 / 0.1720 [139/200][0/29] Loss_D: 1.5166 Loss_G: 6.8525 D(x): 0.9483 D(G(z)): 0.6858 / 0.0032 [140/200][0/29] Loss_D: 0.6012 Loss_G: 3.7446 D(x): 0.8079 D(G(z)): 0.2437 / 0.0646 [141/200][0/29] Loss_D: 0.3333 Loss_G: 7.9246 D(x): 0.9852 D(G(z)): 0.2118 / 0.0017 [142/200][0/29] Loss_D: 0.7650 Loss_G: 2.5486 D(x): 0.8452 D(G(z)): 0.3621 / 0.1274 [143/200][0/29] Loss_D: 0.4099 Loss_G: 4.5433 D(x): 0.8585 D(G(z)): 0.1821 / 0.0199 [144/200][0/29] Loss_D: 0.4872 Loss_G: 4.2445 D(x): 0.8085 D(G(z)): 0.1744 / 0.0333 [145/200][0/29] Loss_D: 0.3651 Loss_G: 4.6325 D(x): 0.8702 D(G(z)): 0.1400 / 0.0205 [146/200][0/29] Loss_D: 2.8417 Loss_G: 6.7404 D(x): 0.1457 D(G(z)): 0.0007 / 0.0425 [147/200][0/29] Loss_D: 2.5167 Loss_G: 7.1884 D(x): 0.9839 D(G(z)): 0.8545 / 0.0055 [148/200][0/29] Loss_D: 0.8964 Loss_G: 1.2590 D(x): 0.6174 D(G(z)): 0.1768 / 0.3568 [149/200][0/29] Loss_D: 0.6820 Loss_G: 3.9271 D(x): 0.6326 D(G(z)): 0.0668 / 0.0535 [150/200][0/29] Loss_D: 1.8979 Loss_G: 9.1887 D(x): 0.9950 D(G(z)): 0.7415 / 0.0007 [151/200][0/29] Loss_D: 0.9859 Loss_G: 6.0849 D(x): 0.9365 D(G(z)): 0.4622 / 0.0084 [152/200][0/29] Loss_D: 0.5578 Loss_G: 6.1723 D(x): 0.9274 D(G(z)): 0.3115 / 0.0067 [153/200][0/29] Loss_D: 0.2158 Loss_G: 5.3003 D(x): 0.9390 D(G(z)): 0.0860 / 0.0126 [154/200][0/29] Loss_D: 0.4628 Loss_G: 7.5250 D(x): 0.9516 D(G(z)): 0.2503 / 0.0028 [155/200][0/29] Loss_D: 0.9081 Loss_G: 5.3791 D(x): 0.5726 D(G(z)): 0.0137 / 0.0285 [156/200][0/29] Loss_D: 0.3874 Loss_G: 3.8241 D(x): 0.8557 D(G(z)): 0.1571 / 0.0534 [157/200][0/29] Loss_D: 0.6303 Loss_G: 2.5302 D(x): 0.6580 D(G(z)): 0.0685 / 0.1787 [158/200][0/29] Loss_D: 1.0661 Loss_G: 7.3054 D(x): 0.9680 D(G(z)): 0.5191 / 0.0027 [159/200][0/29] Loss_D: 0.6059 Loss_G: 12.8963 D(x): 0.9664 D(G(z)): 0.3512 / 0.0002 [160/200][0/29] Loss_D: 0.2949 Loss_G: 4.7012 D(x): 0.8601 D(G(z)): 0.1010 / 0.0246 [161/200][0/29] Loss_D: 0.3380 Loss_G: 3.9627 D(x): 0.8722 D(G(z)): 0.1446 / 0.0416 [162/200][0/29] Loss_D: 0.2733 Loss_G: 5.5427 D(x): 0.9569 D(G(z)): 0.1604 / 0.0162 [163/200][0/29] Loss_D: 0.4982 Loss_G: 6.3878 D(x): 0.9402 D(G(z)): 0.2982 / 0.0080 [164/200][0/29] Loss_D: 0.5999 Loss_G: 3.0015 D(x): 0.6625 D(G(z)): 0.0254 / 0.1031 [165/200][0/29] Loss_D: 0.2393 Loss_G: 6.0414 D(x): 0.8570 D(G(z)): 0.0405 / 0.0070 [166/200][0/29] Loss_D: 0.6344 Loss_G: 6.8651 D(x): 0.7999 D(G(z)): 0.2286 / 0.0071 [167/200][0/29] Loss_D: 1.0181 Loss_G: 2.0890 D(x): 0.7256 D(G(z)): 0.2500 / 0.2027 [168/200][0/29] Loss_D: 0.7652 Loss_G: 3.1896 D(x): 0.6888 D(G(z)): 0.1087 / 0.1253 [169/200][0/29] Loss_D: 1.8008 Loss_G: 0.3881 D(x): 0.3184 D(G(z)): 0.0279 / 0.7581 [170/200][0/29] Loss_D: 1.4647 Loss_G: 3.1712 D(x): 0.3770 D(G(z)): 0.0099 / 0.1645 [171/200][0/29] Loss_D: 0.3866 Loss_G: 3.6163 D(x): 0.9417 D(G(z)): 0.2061 / 0.0582 [172/200][0/29] Loss_D: 1.5385 Loss_G: 10.1382 D(x): 0.9877 D(G(z)): 0.6164 / 0.0004 [173/200][0/29] Loss_D: 0.5035 Loss_G: 3.2289 D(x): 0.7159 D(G(z)): 0.0766 / 0.1514 [174/200][0/29] Loss_D: 0.8912 Loss_G: 10.3584 D(x): 0.9543 D(G(z)): 0.4667 / 0.0003 [175/200][0/29] Loss_D: 0.3573 Loss_G: 4.0062 D(x): 0.8039 D(G(z)): 0.0508 / 0.0433 [176/200][0/29] Loss_D: 0.3440 Loss_G: 4.7981 D(x): 0.8207 D(G(z)): 0.0871 / 0.0307 [177/200][0/29] Loss_D: 0.8048 Loss_G: 5.9978 D(x): 0.5690 D(G(z)): 0.0029 / 0.0119 [178/200][0/29] Loss_D: 0.9462 Loss_G: 6.1787 D(x): 0.9267 D(G(z)): 0.3510 / 0.0086 [179/200][0/29] Loss_D: 0.0366 Loss_G: 6.2566 D(x): 0.9825 D(G(z)): 0.0164 / 0.0135 [180/200][0/29] Loss_D: 1.1179 Loss_G: 3.6820 D(x): 0.5724 D(G(z)): 0.0660 / 0.0983 [181/200][0/29] Loss_D: 0.9000 Loss_G: 7.0798 D(x): 0.9540 D(G(z)): 0.4480 / 0.0065 [182/200][0/29] Loss_D: 0.1423 Loss_G: 6.8391 D(x): 0.9680 D(G(z)): 0.0810 / 0.0103 [183/200][0/29] Loss_D: 1.7081 Loss_G: 7.4436 D(x): 0.9891 D(G(z)): 0.6731 / 0.0071 [184/200][0/29] Loss_D: 2.3040 Loss_G: 2.5461 D(x): 0.2316 D(G(z)): 0.0007 / 0.3582 [185/200][0/29] Loss_D: 1.1815 Loss_G: 12.3839 D(x): 0.9920 D(G(z)): 0.4778 / 0.0000 [186/200][0/29] Loss_D: 0.6197 Loss_G: 9.4907 D(x): 0.9822 D(G(z)): 0.3353 / 0.0004 [187/200][0/29] Loss_D: 0.0118 Loss_G: 10.8918 D(x): 0.9891 D(G(z)): 0.0003 / 0.0004 [188/200][0/29] Loss_D: 0.2507 Loss_G: 5.9260 D(x): 0.8640 D(G(z)): 0.0325 / 0.0314 [189/200][0/29] Loss_D: 1.6216 Loss_G: 7.9644 D(x): 0.3297 D(G(z)): 0.0005 / 0.0191 [190/200][0/29] Loss_D: 0.1006 Loss_G: 6.3627 D(x): 0.9734 D(G(z)): 0.0547 / 0.0095 [191/200][0/29] Loss_D: 0.5573 Loss_G: 3.4582 D(x): 0.7901 D(G(z)): 0.1121 / 0.0951 [192/200][0/29] Loss_D: 0.5376 Loss_G: 5.6361 D(x): 0.7106 D(G(z)): 0.0109 / 0.0323 [193/200][0/29] Loss_D: 0.2363 Loss_G: 5.9708 D(x): 0.8560 D(G(z)): 0.0288 / 0.0093 [194/200][0/29] Loss_D: 0.6321 Loss_G: 11.2579 D(x): 0.9524 D(G(z)): 0.3169 / 0.0003 [195/200][0/29] Loss_D: 0.4710 Loss_G: 11.1584 D(x): 0.9265 D(G(z)): 0.2132 / 0.0004 [196/200][0/29] Loss_D: 0.2261 Loss_G: 6.5116 D(x): 0.9634 D(G(z)): 0.1357 / 0.0073 [197/200][0/29] Loss_D: 1.1561 Loss_G: 2.5541 D(x): 0.5643 D(G(z)): 0.0846 / 0.3014 [198/200][0/29] Loss_D: 0.0569 Loss_G: 7.4992 D(x): 0.9790 D(G(z)): 0.0301 / 0.0038 [199/200][0/29] Loss_D: 0.2802 Loss_G: 8.3995 D(x): 0.9877 D(G(z)): 0.1732 / 0.0021
------------------------ Attempt 3 Starting Training Loop... [0/200][0/29] Loss_D: 1.6919 Loss_G: 3.5758 D(x): 0.3966 D(G(z)): 0.4336 / 0.0397 [1/200][0/29] Loss_D: 0.0017 Loss_G: 24.3003 D(x): 0.9983 D(G(z)): 0.0000 / 0.0000 [2/200][0/29] Loss_D: 0.2443 Loss_G: 24.2967 D(x): 0.8415 D(G(z)): 0.0000 / 0.0000 [3/200][0/29] Loss_D: 0.3429 Loss_G: 9.2204 D(x): 0.7760 D(G(z)): 0.0074 / 0.0003 [4/200][0/29] Loss_D: 0.2953 Loss_G: 2.4491 D(x): 0.8370 D(G(z)): 0.0988 / 0.1013 [5/200][0/29] Loss_D: 0.7030 Loss_G: 1.7735 D(x): 0.6478 D(G(z)): 0.2077 / 0.1995 [6/200][0/29] Loss_D: 0.7444 Loss_G: 5.0542 D(x): 0.9334 D(G(z)): 0.4540 / 0.0141 [7/200][0/29] Loss_D: 0.4598 Loss_G: 5.6356 D(x): 0.7155 D(G(z)): 0.0238 / 0.0198 [8/200][0/29] Loss_D: 0.2347 Loss_G: 6.0450 D(x): 0.9129 D(G(z)): 0.1203 / 0.0038 [9/200][0/29] Loss_D: 3.3479 Loss_G: 1.8203 D(x): 0.1113 D(G(z)): 0.0013 / 0.2342 [10/200][0/29] Loss_D: 0.1400 Loss_G: 3.6535 D(x): 0.9264 D(G(z)): 0.0585 / 0.0338 [11/200][0/29] Loss_D: 0.3777 Loss_G: 5.4987 D(x): 0.8467 D(G(z)): 0.1636 / 0.0062 [12/200][0/29] Loss_D: 0.9476 Loss_G: 7.7428 D(x): 0.4697 D(G(z)): 0.0024 / 0.0043 [13/200][0/29] Loss_D: 0.5612 Loss_G: 2.2834 D(x): 0.6270 D(G(z)): 0.0278 / 0.2538 [14/200][0/29] Loss_D: 0.1280 Loss_G: 3.6601 D(x): 0.9235 D(G(z)): 0.0452 / 0.0291 [15/200][0/29] Loss_D: 0.1674 Loss_G: 4.4131 D(x): 0.9187 D(G(z)): 0.0748 / 0.0133 [16/200][0/29] Loss_D: 0.0986 Loss_G: 5.4124 D(x): 0.9581 D(G(z)): 0.0465 / 0.0053 [17/200][0/29] Loss_D: 0.3304 Loss_G: 4.6639 D(x): 0.9160 D(G(z)): 0.1794 / 0.0144 [18/200][0/29] Loss_D: 1.0156 Loss_G: 0.6390 D(x): 0.4691 D(G(z)): 0.0979 / 0.5887 [19/200][0/29] Loss_D: 0.7462 Loss_G: 2.3211 D(x): 0.7894 D(G(z)): 0.3626 / 0.1185 [20/200][0/29] Loss_D: 2.8919 Loss_G: 3.3485 D(x): 0.9691 D(G(z)): 0.9260 / 0.0471 [21/200][0/29] Loss_D: 0.8944 Loss_G: 1.9260 D(x): 0.6665 D(G(z)): 0.3295 / 0.1717 [22/200][0/29] Loss_D: 0.7873 Loss_G: 1.1228 D(x): 0.6001 D(G(z)): 0.1533 / 0.3638 [23/200][0/29] Loss_D: 0.6751 Loss_G: 3.1319 D(x): 0.8347 D(G(z)): 0.3608 / 0.0536 [24/200][0/29] Loss_D: 0.9361 Loss_G: 1.6986 D(x): 0.5244 D(G(z)): 0.1418 / 0.2200 [25/200][0/29] Loss_D: 0.3727 Loss_G: 2.6489 D(x): 0.8543 D(G(z)): 0.1760 / 0.0920 [26/200][0/29] Loss_D: 0.6820 Loss_G: 2.4776 D(x): 0.7977 D(G(z)): 0.3297 / 0.0996 [27/200][0/29] Loss_D: 0.9816 Loss_G: 1.5207 D(x): 0.4584 D(G(z)): 0.0384 / 0.2979 [28/200][0/29] Loss_D: 0.3168 Loss_G: 3.4402 D(x): 0.8262 D(G(z)): 0.1044 / 0.0471 [29/200][0/29] Loss_D: 0.2820 Loss_G: 3.7696 D(x): 0.8584 D(G(z)): 0.1029 / 0.0273 [30/200][0/29] Loss_D: 2.7104 Loss_G: 6.7191 D(x): 0.9551 D(G(z)): 0.9012 / 0.0024 [31/200][0/29] Loss_D: 0.3727 Loss_G: 3.5944 D(x): 0.8283 D(G(z)): 0.1528 / 0.0348 [32/200][0/29] Loss_D: 0.7845 Loss_G: 3.0368 D(x): 0.7629 D(G(z)): 0.3433 / 0.0721 [33/200][0/29] Loss_D: 0.4794 Loss_G: 3.2676 D(x): 0.8472 D(G(z)): 0.2510 / 0.0513 [34/200][0/29] Loss_D: 0.5115 Loss_G: 3.4815 D(x): 0.8319 D(G(z)): 0.2493 / 0.0434 [35/200][0/29] Loss_D: 0.4789 Loss_G: 3.4776 D(x): 0.8148 D(G(z)): 0.2040 / 0.0415 [36/200][0/29] Loss_D: 0.3362 Loss_G: 3.5134 D(x): 0.8276 D(G(z)): 0.1155 / 0.0400 [37/200][0/29] Loss_D: 1.2338 Loss_G: 4.9664 D(x): 0.9303 D(G(z)): 0.6087 / 0.0108 [38/200][0/29] Loss_D: 0.5490 Loss_G: 1.6642 D(x): 0.7092 D(G(z)): 0.1286 / 0.2378 [39/200][0/29] Loss_D: 0.3061 Loss_G: 3.2860 D(x): 0.8947 D(G(z)): 0.1568 / 0.0512 [40/200][0/29] Loss_D: 0.5232 Loss_G: 4.3621 D(x): 0.8423 D(G(z)): 0.2596 / 0.0178 [41/200][0/29] Loss_D: 2.1780 Loss_G: 0.5943 D(x): 0.1677 D(G(z)): 0.0318 / 0.5862 [42/200][0/29] Loss_D: 0.4510 Loss_G: 3.3788 D(x): 0.9623 D(G(z)): 0.3234 / 0.0473 [43/200][0/29] Loss_D: 0.4779 Loss_G: 2.9969 D(x): 0.9461 D(G(z)): 0.3210 / 0.0619 [44/200][0/29] Loss_D: 0.9613 Loss_G: 1.3177 D(x): 0.4882 D(G(z)): 0.1171 / 0.3415 [45/200][0/29] Loss_D: 0.8098 Loss_G: 1.6339 D(x): 0.5082 D(G(z)): 0.0420 / 0.2210 [46/200][0/29] Loss_D: 0.3973 Loss_G: 4.5190 D(x): 0.8042 D(G(z)): 0.1314 / 0.0183 [47/200][0/29] Loss_D: 0.4322 Loss_G: 3.4465 D(x): 0.8704 D(G(z)): 0.2364 / 0.0400 [48/200][0/29] Loss_D: 1.0237 Loss_G: 5.3219 D(x): 0.9580 D(G(z)): 0.5771 / 0.0087 [49/200][0/29] Loss_D: 0.4694 Loss_G: 3.5509 D(x): 0.8891 D(G(z)): 0.2828 / 0.0348 [50/200][0/29] Loss_D: 0.6890 Loss_G: 4.0468 D(x): 0.8843 D(G(z)): 0.3947 / 0.0236 [51/200][0/29] Loss_D: 0.7531 Loss_G: 2.9151 D(x): 0.7321 D(G(z)): 0.2770 / 0.0783 [52/200][0/29] Loss_D: 0.2497 Loss_G: 4.9013 D(x): 0.9282 D(G(z)): 0.1486 / 0.0131 [53/200][0/29] Loss_D: 1.4567 Loss_G: 4.0037 D(x): 0.8785 D(G(z)): 0.6835 / 0.0327 [54/200][0/29] Loss_D: 0.4709 Loss_G: 4.9134 D(x): 0.6586 D(G(z)): 0.0151 / 0.0176 [55/200][0/29] Loss_D: 0.4229 Loss_G: 4.0040 D(x): 0.8786 D(G(z)): 0.2308 / 0.0256 [56/200][0/29] Loss_D: 0.9897 Loss_G: 0.8101 D(x): 0.4325 D(G(z)): 0.0432 / 0.5107 [57/200][0/29] Loss_D: 0.8086 Loss_G: 4.6352 D(x): 0.9010 D(G(z)): 0.4842 / 0.0133 [58/200][0/29] Loss_D: 0.5366 Loss_G: 2.7604 D(x): 0.8013 D(G(z)): 0.2442 / 0.0861 [59/200][0/29] Loss_D: 0.6207 Loss_G: 2.9377 D(x): 0.6690 D(G(z)): 0.1430 / 0.0791 [60/200][0/29] Loss_D: 0.4540 Loss_G: 3.5037 D(x): 0.9192 D(G(z)): 0.2740 / 0.0470 [61/200][0/29] Loss_D: 0.9069 Loss_G: 1.8625 D(x): 0.4726 D(G(z)): 0.0455 / 0.1994 [62/200][0/29] Loss_D: 0.8963 Loss_G: 0.8906 D(x): 0.4912 D(G(z)): 0.0951 / 0.4766 [63/200][0/29] Loss_D: 0.8233 Loss_G: 0.8737 D(x): 0.5640 D(G(z)): 0.1504 / 0.4618 [64/200][0/29] Loss_D: 0.6732 Loss_G: 3.7945 D(x): 0.9047 D(G(z)): 0.3970 / 0.0322 [65/200][0/29] Loss_D: 0.3086 Loss_G: 3.3587 D(x): 0.8805 D(G(z)): 0.1550 / 0.0482 [66/200][0/29] Loss_D: 0.6541 Loss_G: 4.0405 D(x): 0.9066 D(G(z)): 0.3895 / 0.0252 [67/200][0/29] Loss_D: 0.8442 Loss_G: 4.1337 D(x): 0.4918 D(G(z)): 0.0108 / 0.0268 [68/200][0/29] Loss_D: 0.4523 Loss_G: 2.3963 D(x): 0.7140 D(G(z)): 0.0765 / 0.1263 [69/200][0/29] Loss_D: 0.9388 Loss_G: 4.5463 D(x): 0.9774 D(G(z)): 0.5620 / 0.0149 [70/200][0/29] Loss_D: 0.4129 Loss_G: 3.2654 D(x): 0.8398 D(G(z)): 0.1917 / 0.0514 [71/200][0/29] Loss_D: 0.5553 Loss_G: 2.2811 D(x): 0.6242 D(G(z)): 0.0231 / 0.1286 [72/200][0/29] Loss_D: 0.9827 Loss_G: 2.1069 D(x): 0.4841 D(G(z)): 0.0262 / 0.1597 [73/200][0/29] Loss_D: 0.6984 Loss_G: 4.0612 D(x): 0.9133 D(G(z)): 0.4055 / 0.0275 [74/200][0/29] Loss_D: 0.5455 Loss_G: 2.6654 D(x): 0.8393 D(G(z)): 0.2746 / 0.0939 [75/200][0/29] Loss_D: 0.3162 Loss_G: 4.0582 D(x): 0.8291 D(G(z)): 0.0953 / 0.0257 [76/200][0/29] Loss_D: 0.7308 Loss_G: 2.3281 D(x): 0.5392 D(G(z)): 0.0256 / 0.1525 [77/200][0/29] Loss_D: 0.7276 Loss_G: 1.6552 D(x): 0.6123 D(G(z)): 0.1228 / 0.2417 [78/200][0/29] Loss_D: 0.3426 Loss_G: 3.7327 D(x): 0.8579 D(G(z)): 0.1586 / 0.0306 [79/200][0/29] Loss_D: 0.3377 Loss_G: 3.1353 D(x): 0.8719 D(G(z)): 0.1482 / 0.0635 [80/200][0/29] Loss_D: 1.0110 Loss_G: 6.0048 D(x): 0.9707 D(G(z)): 0.5483 / 0.0049 [81/200][0/29] Loss_D: 0.5030 Loss_G: 4.4006 D(x): 0.9228 D(G(z)): 0.3140 / 0.0229 [82/200][0/29] Loss_D: 0.8281 Loss_G: 5.7145 D(x): 0.9211 D(G(z)): 0.4862 / 0.0051 [83/200][0/29] Loss_D: 0.3612 Loss_G: 2.8661 D(x): 0.8165 D(G(z)): 0.1268 / 0.0753 [84/200][0/29] Loss_D: 0.3017 Loss_G: 3.8754 D(x): 0.8568 D(G(z)): 0.1192 / 0.0342 [85/200][0/29] Loss_D: 0.5822 Loss_G: 3.2599 D(x): 0.7959 D(G(z)): 0.2639 / 0.0555 [86/200][0/29] Loss_D: 0.3042 Loss_G: 2.7522 D(x): 0.8623 D(G(z)): 0.1320 / 0.0851 [87/200][0/29] Loss_D: 0.3411 Loss_G: 3.5200 D(x): 0.8359 D(G(z)): 0.1256 / 0.0428 [88/200][0/29] Loss_D: 0.2497 Loss_G: 3.1211 D(x): 0.9118 D(G(z)): 0.1358 / 0.0657 [89/200][0/29] Loss_D: 0.4030 Loss_G: 3.1789 D(x): 0.8167 D(G(z)): 0.1557 / 0.0641 [90/200][0/29] Loss_D: 0.6020 Loss_G: 5.3412 D(x): 0.9783 D(G(z)): 0.3850 / 0.0096 [91/200][0/29] Loss_D: 0.3347 Loss_G: 3.7150 D(x): 0.8099 D(G(z)): 0.0988 / 0.0339 [92/200][0/29] Loss_D: 0.5496 Loss_G: 4.1633 D(x): 0.6265 D(G(z)): 0.0128 / 0.0459 [93/200][0/29] Loss_D: 0.3594 Loss_G: 3.6608 D(x): 0.9074 D(G(z)): 0.2083 / 0.0356 [94/200][0/29] Loss_D: 1.6572 Loss_G: 5.9731 D(x): 0.9866 D(G(z)): 0.7088 / 0.0066 [95/200][0/29] Loss_D: 1.6805 Loss_G: 5.7784 D(x): 0.9925 D(G(z)): 0.7583 / 0.0065 [96/200][0/29] Loss_D: 0.1611 Loss_G: 2.8033 D(x): 0.9143 D(G(z)): 0.0637 / 0.0790 [97/200][0/29] Loss_D: 0.5304 Loss_G: 4.3010 D(x): 0.8243 D(G(z)): 0.2553 / 0.0208 [98/200][0/29] Loss_D: 0.4506 Loss_G: 5.7690 D(x): 0.9663 D(G(z)): 0.3121 / 0.0051 [99/200][0/29] Loss_D: 0.2274 Loss_G: 3.7448 D(x): 0.8778 D(G(z)): 0.0795 / 0.0446 [100/200][0/29] Loss_D: 0.2278 Loss_G: 2.2476 D(x): 0.8756 D(G(z)): 0.0773 / 0.1568 [101/200][0/29] Loss_D: 1.0943 Loss_G: 6.9977 D(x): 0.9743 D(G(z)): 0.5940 / 0.0025 [102/200][0/29] Loss_D: 0.1414 Loss_G: 4.6583 D(x): 0.9283 D(G(z)): 0.0590 / 0.0141 [103/200][0/29] Loss_D: 0.6926 Loss_G: 6.1033 D(x): 0.9566 D(G(z)): 0.4306 / 0.0052 [104/200][0/29] Loss_D: 0.5699 Loss_G: 5.6320 D(x): 0.9708 D(G(z)): 0.3745 / 0.0053 [105/200][0/29] Loss_D: 0.8684 Loss_G: 2.0502 D(x): 0.5175 D(G(z)): 0.0075 / 0.1730 [106/200][0/29] Loss_D: 0.6212 Loss_G: 6.1123 D(x): 0.9564 D(G(z)): 0.3929 / 0.0034 [107/200][0/29] Loss_D: 0.1547 Loss_G: 3.1552 D(x): 0.9347 D(G(z)): 0.0785 / 0.0638 [108/200][0/29] Loss_D: 0.2084 Loss_G: 3.0026 D(x): 0.9373 D(G(z)): 0.1165 / 0.0955 [109/200][0/29] Loss_D: 0.6049 Loss_G: 4.5160 D(x): 0.9832 D(G(z)): 0.3706 / 0.0178 [110/200][0/29] Loss_D: 0.3379 Loss_G: 3.1584 D(x): 0.8723 D(G(z)): 0.1659 / 0.0623 [111/200][0/29] Loss_D: 0.4187 Loss_G: 5.1438 D(x): 0.9612 D(G(z)): 0.2859 / 0.0089 [112/200][0/29] Loss_D: 0.7236 Loss_G: 6.8368 D(x): 0.9902 D(G(z)): 0.4512 / 0.0021 [113/200][0/29] Loss_D: 0.1992 Loss_G: 3.9624 D(x): 0.9835 D(G(z)): 0.1477 / 0.0291 [114/200][0/29] Loss_D: 0.5511 Loss_G: 5.0258 D(x): 0.9584 D(G(z)): 0.3571 / 0.0100 [115/200][0/29] Loss_D: 0.3889 Loss_G: 4.6397 D(x): 0.9744 D(G(z)): 0.2746 / 0.0175 [116/200][0/29] Loss_D: 0.5926 Loss_G: 5.3438 D(x): 0.9558 D(G(z)): 0.3687 / 0.0081 [117/200][0/29] Loss_D: 0.3317 Loss_G: 3.9607 D(x): 0.9645 D(G(z)): 0.2254 / 0.0275 [118/200][0/29] Loss_D: 0.4744 Loss_G: 5.3757 D(x): 0.9774 D(G(z)): 0.3062 / 0.0084 [119/200][0/29] Loss_D: 0.1221 Loss_G: 3.8970 D(x): 0.9377 D(G(z)): 0.0527 / 0.0355 [120/200][0/29] Loss_D: 2.8506 Loss_G: 7.3343 D(x): 0.9916 D(G(z)): 0.9023 / 0.0016 [121/200][0/29] Loss_D: 0.2626 Loss_G: 2.8696 D(x): 0.8590 D(G(z)): 0.0932 / 0.0804 [122/200][0/29] Loss_D: 0.6766 Loss_G: 1.4965 D(x): 0.5990 D(G(z)): 0.0781 / 0.2875 [123/200][0/29] Loss_D: 0.4316 Loss_G: 2.3644 D(x): 0.6976 D(G(z)): 0.0302 / 0.1335 [124/200][0/29] Loss_D: 0.3812 Loss_G: 4.6432 D(x): 0.9814 D(G(z)): 0.2869 / 0.0144 [125/200][0/29] Loss_D: 0.3022 Loss_G: 3.3826 D(x): 0.8782 D(G(z)): 0.1429 / 0.0507 [126/200][0/29] Loss_D: 0.5513 Loss_G: 2.5618 D(x): 0.6380 D(G(z)): 0.0230 / 0.1342 [127/200][0/29] Loss_D: 0.3456 Loss_G: 4.1876 D(x): 0.9493 D(G(z)): 0.2343 / 0.0210 [128/200][0/29] Loss_D: 0.1288 Loss_G: 4.4410 D(x): 0.9483 D(G(z)): 0.0675 / 0.0181 [129/200][0/29] Loss_D: 0.6023 Loss_G: 6.5510 D(x): 0.9866 D(G(z)): 0.3979 / 0.0026 [130/200][0/29] Loss_D: 0.6231 Loss_G: 3.3214 D(x): 0.9407 D(G(z)): 0.3692 / 0.0634 [131/200][0/29] Loss_D: 0.3662 Loss_G: 2.5155 D(x): 0.7889 D(G(z)): 0.0932 / 0.1226 [132/200][0/29] Loss_D: 0.5270 Loss_G: 2.1233 D(x): 0.6369 D(G(z)): 0.0113 / 0.1751 [133/200][0/29] Loss_D: 0.2918 Loss_G: 4.0943 D(x): 0.9320 D(G(z)): 0.1853 / 0.0257 [134/200][0/29] Loss_D: 0.4416 Loss_G: 4.5842 D(x): 0.9445 D(G(z)): 0.2918 / 0.0223 [135/200][0/29] Loss_D: 0.1340 Loss_G: 3.7435 D(x): 0.9505 D(G(z)): 0.0751 / 0.0358 [136/200][0/29] Loss_D: 1.8295 Loss_G: 7.4098 D(x): 0.9962 D(G(z)): 0.7206 / 0.0026 [137/200][0/29] Loss_D: 0.3794 Loss_G: 2.9927 D(x): 0.7478 D(G(z)): 0.0555 / 0.0854 [138/200][0/29] Loss_D: 0.1477 Loss_G: 4.8500 D(x): 0.9104 D(G(z)): 0.0451 / 0.0140 [139/200][0/29] Loss_D: 0.1892 Loss_G: 3.2492 D(x): 0.9066 D(G(z)): 0.0811 / 0.0535 [140/200][0/29] Loss_D: 0.1827 Loss_G: 3.0683 D(x): 0.9484 D(G(z)): 0.1137 / 0.0707 [141/200][0/29] Loss_D: 0.2072 Loss_G: 3.5212 D(x): 0.9252 D(G(z)): 0.1116 / 0.0481 [142/200][0/29] Loss_D: 0.2802 Loss_G: 5.6606 D(x): 0.7878 D(G(z)): 0.0080 / 0.0113 [143/200][0/29] Loss_D: 0.2968 Loss_G: 3.9169 D(x): 0.8083 D(G(z)): 0.0512 / 0.0372 [144/200][0/29] Loss_D: 0.2745 Loss_G: 4.0905 D(x): 0.8095 D(G(z)): 0.0415 / 0.0317 [145/200][0/29] Loss_D: 0.1456 Loss_G: 3.6782 D(x): 0.9031 D(G(z)): 0.0379 / 0.0383 [146/200][0/29] Loss_D: 3.2540 Loss_G: 9.6398 D(x): 0.9992 D(G(z)): 0.9206 / 0.0004 [147/200][0/29] Loss_D: 0.6006 Loss_G: 5.7920 D(x): 0.9768 D(G(z)): 0.3687 / 0.0074 [148/200][0/29] Loss_D: 0.3326 Loss_G: 4.2664 D(x): 0.9268 D(G(z)): 0.2026 / 0.0242 [149/200][0/29] Loss_D: 0.1659 Loss_G: 3.8353 D(x): 0.9511 D(G(z)): 0.1036 / 0.0323 [150/200][0/29] Loss_D: 0.1852 Loss_G: 3.0983 D(x): 0.8667 D(G(z)): 0.0343 / 0.0757 [151/200][0/29] Loss_D: 0.4448 Loss_G: 4.8393 D(x): 0.9477 D(G(z)): 0.2830 / 0.0148 [152/200][0/29] Loss_D: 0.3797 Loss_G: 5.9062 D(x): 0.9650 D(G(z)): 0.2520 / 0.0056 [153/200][0/29] Loss_D: 0.2142 Loss_G: 3.1126 D(x): 0.8888 D(G(z)): 0.0817 / 0.0595 [154/200][0/29] Loss_D: 0.1375 Loss_G: 4.4360 D(x): 0.9096 D(G(z)): 0.0331 / 0.0261 [155/200][0/29] Loss_D: 0.2435 Loss_G: 3.3263 D(x): 0.8422 D(G(z)): 0.0486 / 0.0586 [156/200][0/29] Loss_D: 0.1523 Loss_G: 3.9945 D(x): 0.8893 D(G(z)): 0.0238 / 0.0329 [157/200][0/29] Loss_D: 0.7794 Loss_G: 6.0971 D(x): 0.9698 D(G(z)): 0.4353 / 0.0045 [158/200][0/29] Loss_D: 0.3719 Loss_G: 4.7599 D(x): 0.9812 D(G(z)): 0.2548 / 0.0166 [159/200][0/29] Loss_D: 2.0389 Loss_G: 10.1373 D(x): 0.9928 D(G(z)): 0.7327 / 0.0004 [160/200][0/29] Loss_D: 0.3568 Loss_G: 4.0789 D(x): 0.8788 D(G(z)): 0.1754 / 0.0296 [161/200][0/29] Loss_D: 0.2395 Loss_G: 3.2149 D(x): 0.8896 D(G(z)): 0.1003 / 0.0607 [162/200][0/29] Loss_D: 0.3788 Loss_G: 3.9503 D(x): 0.9729 D(G(z)): 0.2715 / 0.0274 [163/200][0/29] Loss_D: 0.1468 Loss_G: 3.7616 D(x): 0.9356 D(G(z)): 0.0727 / 0.0372 [164/200][0/29] Loss_D: 0.1612 Loss_G: 3.9790 D(x): 0.9419 D(G(z)): 0.0905 / 0.0293 [165/200][0/29] Loss_D: 0.7553 Loss_G: 7.7398 D(x): 0.9930 D(G(z)): 0.4488 / 0.0008 [166/200][0/29] Loss_D: 0.1678 Loss_G: 3.7915 D(x): 0.9135 D(G(z)): 0.0685 / 0.0360 [167/200][0/29] Loss_D: 0.0980 Loss_G: 4.2978 D(x): 0.9439 D(G(z)): 0.0372 / 0.0249 [168/200][0/29] Loss_D: 0.0954 Loss_G: 4.6805 D(x): 0.9524 D(G(z)): 0.0423 / 0.0160 [169/200][0/29] Loss_D: 0.1297 Loss_G: 3.5591 D(x): 0.9560 D(G(z)): 0.0758 / 0.0496 [170/200][0/29] Loss_D: 1.1637 Loss_G: 1.9073 D(x): 0.5178 D(G(z)): 0.2003 / 0.3122 [171/200][0/29] Loss_D: 0.5310 Loss_G: 4.3686 D(x): 0.9302 D(G(z)): 0.3291 / 0.0186 [172/200][0/29] Loss_D: 0.2821 Loss_G: 2.9949 D(x): 0.8155 D(G(z)): 0.0593 / 0.0763 [173/200][0/29] Loss_D: 0.2264 Loss_G: 3.8713 D(x): 0.8707 D(G(z)): 0.0723 / 0.0348 [174/200][0/29] Loss_D: 0.2194 Loss_G: 3.0420 D(x): 0.9038 D(G(z)): 0.1003 / 0.0703 [175/200][0/29] Loss_D: 0.2372 Loss_G: 3.0622 D(x): 0.8983 D(G(z)): 0.1081 / 0.0733 [176/200][0/29] Loss_D: 0.2624 Loss_G: 4.0727 D(x): 0.9720 D(G(z)): 0.1907 / 0.0274 [177/200][0/29] Loss_D: 0.2331 Loss_G: 3.7759 D(x): 0.8495 D(G(z)): 0.0409 / 0.0515 [178/200][0/29] Loss_D: 0.3835 Loss_G: 2.6801 D(x): 0.7612 D(G(z)): 0.0775 / 0.1033 [179/200][0/29] Loss_D: 0.1967 Loss_G: 3.7066 D(x): 0.9374 D(G(z)): 0.1127 / 0.0390 [180/200][0/29] Loss_D: 0.5053 Loss_G: 5.3566 D(x): 0.9192 D(G(z)): 0.2887 / 0.0118 [181/200][0/29] Loss_D: 0.2325 Loss_G: 3.8824 D(x): 0.9609 D(G(z)): 0.1570 / 0.0313 [182/200][0/29] Loss_D: 0.6169 Loss_G: 3.0302 D(x): 0.6255 D(G(z)): 0.0151 / 0.1141 [183/200][0/29] Loss_D: 0.4280 Loss_G: 6.1672 D(x): 0.9612 D(G(z)): 0.2778 / 0.0032 [184/200][0/29] Loss_D: 0.3192 Loss_G: 4.3766 D(x): 0.8395 D(G(z)): 0.0986 / 0.0231 [185/200][0/29] Loss_D: 0.1891 Loss_G: 3.5325 D(x): 0.9007 D(G(z)): 0.0707 / 0.0484 [186/200][0/29] Loss_D: 0.1737 Loss_G: 3.9259 D(x): 0.9747 D(G(z)): 0.1269 / 0.0276 [187/200][0/29] Loss_D: 1.9621 Loss_G: 9.3239 D(x): 0.9766 D(G(z)): 0.7380 / 0.0003 [188/200][0/29] Loss_D: 0.1817 Loss_G: 4.1876 D(x): 0.9078 D(G(z)): 0.0734 / 0.0252 [189/200][0/29] Loss_D: 0.2697 Loss_G: 3.2769 D(x): 0.8454 D(G(z)): 0.0819 / 0.0590 [190/200][0/29] Loss_D: 0.2039 Loss_G: 3.2097 D(x): 0.9446 D(G(z)): 0.1240 / 0.0690 [191/200][0/29] Loss_D: 0.1162 Loss_G: 3.4329 D(x): 0.9729 D(G(z)): 0.0807 / 0.0485 [192/200][0/29] Loss_D: 0.2079 Loss_G: 3.9653 D(x): 0.8834 D(G(z)): 0.0720 / 0.0330 [193/200][0/29] Loss_D: 0.1961 Loss_G: 3.5648 D(x): 0.9383 D(G(z)): 0.1159 / 0.0438 [194/200][0/29] Loss_D: 0.3211 Loss_G: 3.1483 D(x): 0.8591 D(G(z)): 0.1144 / 0.0879 [195/200][0/29] Loss_D: 0.2123 Loss_G: 4.5620 D(x): 0.9694 D(G(z)): 0.1527 / 0.0165 [196/200][0/29] Loss_D: 0.1626 Loss_G: 4.9394 D(x): 0.9811 D(G(z)): 0.1244 / 0.0111 [197/200][0/29] Loss_D: 0.1073 Loss_G: 3.9928 D(x): 0.9204 D(G(z)): 0.0203 / 0.0324 [198/200][0/29] Loss_D: 0.1109 Loss_G: 4.3211 D(x): 0.9711 D(G(z)): 0.0737 / 0.0218 [199/200][0/29] Loss_D: 0.3434 Loss_G: 5.3806 D(x): 0.9279 D(G(z)): 0.2140 / 0.0077
------------------------ Attempt 4 Starting Training Loop... [0/400][0/29] Loss_D: 1.3558 Loss_G: 29.2974 D(x): 0.4940 D(G(z)): 0.3844 / 0.0000 [1/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [2/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [3/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [4/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [5/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [6/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [7/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [8/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [9/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [10/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [11/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [12/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [13/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [14/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [15/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [16/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [17/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [18/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [19/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [20/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [21/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [22/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [23/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [24/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [25/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [26/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [27/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [28/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [29/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [30/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [31/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [32/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [33/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [34/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [35/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [36/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [37/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [38/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [39/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [40/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [41/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [42/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [43/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [44/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [45/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [46/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [47/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [48/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [49/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [50/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [51/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [52/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [53/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [54/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [55/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [56/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [57/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [58/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [59/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [60/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [61/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [62/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [63/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [64/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [65/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [66/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [67/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [68/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [69/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [70/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [71/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [72/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [73/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [74/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [75/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [76/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [77/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [78/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [79/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [80/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [81/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [82/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [83/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [84/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [85/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [86/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [87/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [88/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [89/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [90/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [91/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [92/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [93/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [94/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [95/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [96/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [97/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [98/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [99/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [100/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [101/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [102/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [103/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [104/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [105/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [106/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [107/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [108/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [109/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [110/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [111/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [112/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [113/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [114/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [115/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [116/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [117/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [118/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [119/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [120/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [121/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [122/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [123/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [124/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [125/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [126/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [127/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [128/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [129/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [130/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [131/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [132/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [133/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [134/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [135/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [136/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [137/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [138/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [139/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [140/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [141/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [142/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [143/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [144/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [145/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [146/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [147/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [148/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [149/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [150/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [151/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [152/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [153/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [154/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [155/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [156/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [157/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [158/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [159/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [160/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [161/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [162/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [163/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [164/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [165/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [166/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [167/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [168/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [169/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [170/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [171/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [172/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [173/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [174/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [175/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [176/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [177/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [178/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [179/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [180/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [181/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [182/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [183/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [184/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [185/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [186/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [187/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [188/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [189/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [190/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [191/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [192/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [193/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [194/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [195/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [196/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [197/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [198/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000 [199/400][0/29] Loss_D: 27.6310 Loss_G: 0.0000 D(x): 1.0000 D(G(z)): 1.0000 / 1.0000
--------------------------------------- KeyboardInterruptTraceback (most recent call last) <timed exec> in <module> ~/gan_plankton/src/models/models.py in train(self, dataloader, num_epochs) 144 for epoch in range(num_epochs): 145 # For each batch in the dataloader --> 146 for i, data in enumerate(dataloader, 0): 147 148 ############################ ~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in __next__(self) 343 344 def __next__(self): --> 345 data = self._next_data() 346 self._num_yielded += 1 347 if self._dataset_kind == _DatasetKind.Iterable and \ ~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _next_data(self) 839 840 assert not self._shutdown and self._tasks_outstanding > 0 --> 841 idx, data = self._get_data() 842 self._tasks_outstanding -= 1 843 ~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _get_data(self) 806 else: 807 while True: --> 808 success, data = self._try_get_data() 809 if success: 810 return data ~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _try_get_data(self, timeout) 759 # (bool: whether successfully get data, any: data if successful else None) 760 try: --> 761 data = self._data_queue.get(timeout=timeout) 762 return (True, data) 763 except Exception as e: ~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py in get(self, block, timeout) 105 if block: 106 timeout = deadline - time.monotonic() --> 107 if not self._poll(timeout): 108 raise Empty 109 elif not self._poll(): ~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in poll(self, timeout) 255 self._check_closed() 256 self._check_readable() --> 257 return self._poll(timeout) 258 259 def __enter__(self): ~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in _poll(self, timeout) 422 423 def _poll(self, timeout): --> 424 r = wait([self], timeout) 425 return bool(r) 426 ~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in wait(object_list, timeout) 928 929 while True: --> 930 ready = selector.select(timeout) 931 if ready: 932 return [key.fileobj for (key, events) in ready] ~/anaconda3/envs/ganenv/lib/python3.8/selectors.py in select(self, timeout) 413 ready = [] 414 try: --> 415 fd_event_list = self._selector.poll(timeout) 416 except InterruptedError: 417 return ready KeyboardInterrupt:
Visualize training stats¶
In [ ]:
plot_loss(gan.G_losses, gan.D_losses)
In [ ]:
generator_progress(gan.img_list)
In [ ]:
compare_fake_real(data_loader, gan.device, gan.img_list)
Use models¶
In [ ]:
fake_batch = gan.generate(torch.randn(64, gan.generator.latent_size, 1, 1, device=gan.device))
print_batch_images([fake_batch], gan.device)
In [ ]:
gan.predict_discriminator(next(iter(data_loader))[0])